Homework 1

Author

Anja

Published

September 8, 2024

Load Packages

library(Hmisc)
library(tidyverse)

Problem 1

Survey

August 29, 2024 at 9:44pm.

Campuswire

Insert the image you uploaded to Campuswire here.

This image shows top portion of the editor pane in RStudio with the image icon circled in red

How to insert an image into a Quarto document

Problem 2

Question 1

The study population of data set 1 is people in the UK that have experience with crime. The study population of data set 2 is crimes that were reported.

Question 2

In data set 1, the answers reported were voluntary and self reported. In data set 2, is convenient sampling because the records had been reported by the UK police.

Question 3

The first data set was a survey of people that are 16 years of age or older that are not living in communal residences (self reported). The second data set is recorded crimes by the UK police.

Question 4

The target population in data set 1 is how much crime rates in UK.

Question 5

In data set one, it is not very valid nor reliable due to self reporting and how answers could be biased. In data set 2, it is reliable and valid because the crimes have been reported and administrated by the UK police, which make them a valid and reliable source. The conclusion on data set 1 will not be generalizable because the self reports may not be the same for everyone. The conclusions for data set 2 can be generalizable and can make the conclusion whether crime rates have gone up or down, only if the police definition of crimes has not changed over time.

Problem 3

Question 1

The <- notation is equivalent to an = sign in R and is often used to declare variables. After running this code chunk, the named dataframe df appears in the environment on the right-hand side of RStudio.

df <- read_csv('https://www.openintro.org/data/csv/babies.csv')
Rows: 1236 Columns: 8
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (8): case, bwt, gestation, parity, age, height, weight, smoke

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Question 2

The notation Hmisc:: directly calls this function from the Hmisc package. describe() is a common function name, and sometimes this is needed to indicate to R which function from which package you want to use. The pipe feature |> sends the results of the first line directly into the function on the 2nd line and is a convenient way to chain functions together.

This code prints a useful and attractive summary of the data set we are using.

Hmisc::describe(df) |> 
  html()
df Descriptives
df

8 Variables   1236 Observations
case
image
        n  missing distinct     Info     Mean      Gmd      .05      .10      .25 
     1236        0     1236        1    618.5    412.3    62.75   124.50   309.75 
      .50      .75      .90      .95 
   618.50   927.25  1112.50  1174.25
lowest : 1 2 3 4 5 , highest: 1232 1233 1234 1235 1236
bwt
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
123601071119.620.33 88.0 97.0108.8120.0131.0142.0149.0
lowest : 55 58 62 63 65 , highest: 169 170 173 174 176
gestation
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
1223131060.999279.316.57252.0262.0272.0280.0288.0295.8302.0
lowest : 148 181 204 223 224 , highest: 330 336 338 351 353
parity
nmissingdistinctInfoSumMeanGmd
1236020.573150.25490.3801
age
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
12342300.99727.266.50619202326313638
lowest : 15 17 18 19 20 , highest: 41 42 43 44 45
height
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
121422190.98664.052.83960616264666768
 Value         53    54    56    57    58    59    60    61    62    63    64    65
 Frequency      1     1     1     1    10    26    55   105   131   166   183   182
 Proportion 0.001 0.001 0.001 0.001 0.008 0.021 0.045 0.086 0.108 0.137 0.151 0.150
                                                     
 Value         66    67    68    69    70    71    72
 Frequency    153   105    54    20    13     6     1
 Proportion 0.126 0.086 0.044 0.016 0.011 0.005 0.001
For the frequency table, variable is rounded to the nearest 0
weight
image
nmissingdistinctInfoMeanGmd.05.10.25.50.75.90.95
1200361050.999128.622.39102.0105.0114.8125.0139.0155.0170.0
lowest : 87 89 90 91 92 , highest: 215 217 220 228 250
smoke
nmissingdistinctInfoSumMeanGmd
12261020.7174840.39480.4782

Question 3

The Child Health and Development Studies investigate a range of topics. One study, in particular, considered all pregnancies between 1960 and 1967 among women in the Kaiser Foundation Health Plan in the San Francisco East Bay area. The variables in this data set are as follows.

Data Dictionary
Variable Name Variable Description Variable Type
case id number num discrete
bwt birthweight, in ounces num continuous
gestation length of gestation, in days num continuous
parity binary indicator for a first pregnancy (0 = first pregnancy) categorical binary
age mother’s age in years num continuous
height mother’s height in inches

num

ordinal
weight mother’s weight in pounds num continuous
smoke binary indicator for whether the mother smokes categorical binary

Question 4

Below, 2 numeric variables were investigated for potential relationships. The independent, explanatory variable I chose is variable_name, and the dependent, response variable I chose is variable_name.

df |>
  ggplot(aes(x = gestation, # please change these
              y = bwt)) + 
  geom_point()
Warning: Removed 13 rows containing missing values or values outside the scale range
(`geom_point()`).

Describe what you see in your plot here.

The gestation points are between 250-300 days. It looks like as gestation gets longer, birth weight goes up as well. This means they are related. Gestation and birth weight have similar data since the graph has one big black spot.

Session Info

This portion of the document describes the conditions in RStudio under which this report was created. This is important to include so that work is reproducible by others.

xfun::session_info()
R version 4.4.1 (2024-06-14)
Platform: aarch64-apple-darwin20
Running under: macOS Sonoma 14.5

Locale: en_US.UTF-8 / en_US.UTF-8 / en_US.UTF-8 / C / en_US.UTF-8 / en_US.UTF-8

Package version:
  askpass_1.2.0       backports_1.5.0     base64enc_0.1-3    
  bit_4.0.5           bit64_4.0.5         blob_1.2.4         
  broom_1.0.6         bslib_0.8.0         cachem_1.1.0       
  callr_3.7.6         cellranger_1.1.0    checkmate_2.3.2    
  cli_3.6.3           clipr_0.8.0         cluster_2.1.6      
  colorspace_2.1-1    compiler_4.4.1      conflicted_1.2.0   
  cpp11_0.4.7         crayon_1.5.3        curl_5.2.1         
  data.table_1.15.4   DBI_1.2.3           dbplyr_2.5.0       
  digest_0.6.37       dplyr_1.1.4         dtplyr_1.3.1       
  evaluate_0.24.0     fansi_1.0.6         farver_2.1.2       
  fastmap_1.2.0       fontawesome_0.5.2   forcats_1.0.0      
  foreign_0.8-86      Formula_1.2-5       fs_1.6.4           
  gargle_1.5.2        generics_0.1.3      ggplot2_3.5.1      
  glue_1.7.0          googledrive_2.1.1   googlesheets4_1.1.1
  graphics_4.4.1      grDevices_4.4.1     grid_4.4.1         
  gridExtra_2.3       gtable_0.3.5        haven_2.5.4        
  highr_0.11          Hmisc_5.1-3         hms_1.1.3          
  htmlTable_2.4.3     htmltools_0.5.8.1   htmlwidgets_1.6.4  
  httr_1.4.7          ids_1.0.1           isoband_0.2.7      
  jquerylib_0.1.4     jsonlite_1.8.8      knitr_1.48         
  labeling_0.4.3      lattice_0.22.6      lifecycle_1.0.4    
  lubridate_1.9.3     magrittr_2.0.3      MASS_7.3.60.2      
  Matrix_1.7.0        memoise_2.0.1       methods_4.4.1      
  mgcv_1.9.1          mime_0.12           modelr_0.1.11      
  munsell_0.5.1       nlme_3.1.164        nnet_7.3-19        
  openssl_2.2.1       parallel_4.4.1      pillar_1.9.0       
  pkgconfig_2.0.3     prettyunits_1.2.0   processx_3.8.4     
  progress_1.2.3      ps_1.7.7            purrr_1.0.2        
  R6_2.5.1            ragg_1.3.2          rappdirs_0.3.3     
  RColorBrewer_1.1.3  readr_2.1.5         readxl_1.4.3       
  rematch_2.0.0       rematch2_2.1.2      reprex_2.1.1       
  rlang_1.1.4         rmarkdown_2.28      rpart_4.1.23       
  rstudioapi_0.16.0   rvest_1.0.4         sass_0.4.9         
  scales_1.3.0        selectr_0.4.2       splines_4.4.1      
  stats_4.4.1         stringi_1.8.4       stringr_1.5.1      
  sys_3.4.2           systemfonts_1.1.0   textshaping_0.4.0  
  tibble_3.2.1        tidyr_1.3.1         tidyselect_1.2.1   
  tidyverse_2.0.0     timechange_0.3.0    tinytex_0.52       
  tools_4.4.1         tzdb_0.4.0          utf8_1.2.4         
  utils_4.4.1         uuid_1.2.1          vctrs_0.6.5        
  viridis_0.6.5       viridisLite_0.4.2   vroom_1.6.5        
  withr_3.0.1         xfun_0.47           xml2_1.3.6         
  yaml_2.3.10